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I'm trying to understand Exponentiated Weibull (EW) function ExpoWeibull from package reliaR , however the function only use a single shape parameter and a scale parameter. From what I've read about the EW distribution, a second shape parameter is used. Is there an existing implementation of EW for R, that accepts two shape parameters? If not, how does one go about implementing the distribution function?

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  • $\begingroup$ What is your reference for a second shape parameter? $\endgroup$
    – user81847
    Nov 19, 2015 at 1:13
  • $\begingroup$ @Pascal, I got the information from here: en.wikipedia.org/wiki/Exponentiated_Weibull_distribution I am specifically looking for a way of describing a "bathtub" distribution. $\endgroup$ Nov 19, 2015 at 2:09
  • $\begingroup$ You should search: install.packages("sos", dep = TRUE); library(sos); findFn("Exponentiated Weibull"). Gives, for example, hits for packages bda. $\endgroup$
    – user81847
    Nov 19, 2015 at 2:12
  • $\begingroup$ Or go to CRAN, the CRAN taskview page, Distributions taskview, and search there! $\endgroup$ Jan 22, 2016 at 13:44

2 Answers 2

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I disagree with Brad. The function computed in the reliaR package is correct. It's just the same formula like on Wikipedia. You'll just have to substitute (x/lambda)=x1, k=alpha1 and Alpha=Theta. Just take the cumulative distribution, substitute the 3 variables and derive it! Don't Forget to Substitute dx too! Or have a look at http://www.academia.edu/6178638/Estimation_for_the_Parameters_of_the_Exponentiated_Weibull_Distribution_Based_on_Progressive_Hybrid_Censored_Samples. Page 1714 There you can see: both cumulative function are equal

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As far as I can tell, the function in that package is wrong. I had to code the distribution myself. If lambda is the scale parameter and x and alpha are the shape parameters (going by the notation in Wikipedia for simplicity):

dexpweib=function(x, alpha, k, lambda, log=FALSE){
if ((!is.numeric(x)) || (!is.numeric(alpha))|| (!is.numeric(k)) || (!is.numeric(lambda))){ 
    stop("non-numeric argument to mathematical function")}
if((length(alpha)!= 1) || (length(k)!=1) || (length(lambda)!=1)){
    stop("Non-x parameters must be atomic")}
if ((min(x) <= 0) || (alpha <= 0) || (k <= 0) || (lambda <= 0)){ 
    stop("Invalid arguments. Must be > 0 ")}
u <- exp(-(x/lambda)^k)
pdf <- ((alpha*k)/(lambda^k))*(x^(k-1))*u*((1-u)^(alpha-1))
if (log) 
    pdf <- log(pdf)
return(pdf)

}

pexpweib=function(q, alpha, k, lambda, log.p=FALSE){
if ((!is.numeric(q)) || (!is.numeric(alpha))|| (!is.numeric(k)) || (!is.numeric(lambda))){ 
    stop("non-numeric argument to mathematical function")}
if((length(alpha)!= 1) || (length(k)!=1) || (length(lambda)!=1)){
    stop("Non-q parameters must be atomic")}
if ((min(q) <= 0) || (alpha <= 0) || (k <= 0) || (lambda <= 0)){ 
    stop("Invalid arguments. Must be > 0 ")}
u <- exp(-(q/lambda)^k)
cdf <- (1-u)^alpha
if (log.p) 
    cdf <- log(cdf)
return(cdf)

}

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